sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
eadc783c18a3805b5c1edee4f3f2369469a9b5c007f0057899009c0acb118e82 | Python | 4,013 | 103 | """Rig presets, YAML round trip and the roofline mounting rule (pure parts)."""
import numpy as np
import pytest
import carla
from carla_cosmos import coords
from carla_cosmos.contracts import AV_CAMERAS
from carla_cosmos.rig import Camera, Rig, _apply_mount_rule, rear_axle_xy_from_bones
def test_presets():
av... |
3f7efe837f13d49c0aca969b425383c5225edc21c04e25a009070f8599838911 | Python | 4,014 | 122 |
import torch
import torch.nn as nn
class MoCo(nn.Module):
"""
Build a MoCo model with a base encoder, a momentum encoder, and two MLPs
https://arxiv.org/abs/1911.05722
"""
def __init__(self, base_encoder, dim=256, mlp_dim=4096, T=1.0):
"""
dim: feature dimension (default: 256)
... |
e2ce140bd91a926565f6592101d36c3354020bdd0467a44f15e67a49260bb537 | Python | 4,015 | 66 | """Run the tuto_G_traffic_manager set_path example and record what the vehicles actually drive.
tm_paths.py OUT.json R1S R1(comma) R2S R2(comma) [seconds]"""
import json, random, sys, os
import carla
sys.path.insert(0, os.path.dirname(__file__)); import scene
out, r1s, r1, r2s, r2 = sys.argv[1], int(sys.argv[2]), [int(... |
ef5a202615d645392a49ac208286096f1f96b60e7d42faa084543da0c17f65bf | Python | 4,015 | 117 | # Copyright 2022 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... |
2593b5e30c0b74cb2f0c080bda732dd4ff8a697eff91747810b1c9e55a0691cf | Python | 4,016 | 145 | """
Associating mitochondria to a set of skeleton nodes
More precisely, finding the set of skeleton nodes that is the closest to
some mesh vertex of each mitochondrion. Labels each such mitochondrion
with the set of skeleton node indices that is paired with it in this way.
"""
import sys
import time
import operator
im... |
1775a24b05b37ed4e9b79352cbf0b0e59f4a9d02c9f90af5903de775544dfcfb | Python | 4,017 | 99 | import torch
import torch.nn as nn
import torch.nn.functional as F
import math
from drugex import utils
class Attn(nn.Module):
def __init__(self, h_dim):
super(Attn, self).__init__()
self.h_dim = h_dim
self.main = nn.Sequential(
nn.Linear(h_dim, 100),
nn.ReLU(True),... |
762801294fc92d8727350e652959e4bc4558a097a32b1049431d556d2156fb39 | Python | 4,017 | 122 | import argparse
import os
import autosklearn.classification
import joblib
import medmnist
import numpy as np
from medmnist import INFO, Evaluator
from medmnist.info import DEFAULT_ROOT
def main(data_flag, time, input_root, output_root, run, model_path):
time = time * 60 * 60
info = INFO[data_flag]
... |
98a07db3d39f9b59a41244083f085ebc27c75d35dbc27811e3b693c7aaf1f85b | Python | 4,017 | 120 | ####################################################################################################
# Copyright (c) 2019 - 2023, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of VessMorphoVis <https://github.com/BlueBrain/VessMorphoVis>
#
# This program is free ... |
35398b75843b673559635b7c49d41bd1aa0347a4019cb5943c71446848e37650 | Python | 4,018 | 137 | """
Neighbor Search for Graph Neural Operators
===========================================
This tutorial demonstrates neighbor search algorithms used in Graph Neural Operators (GNO).
Neighbor search is crucial for:
- Finding spatial relationships in irregular point clouds
- Computing Nyström approximations of kernel ... |
f1688006b544aa2bbe0e26b101408456f14c87b82256cb42639f74c4b491b578 | Python | 4,018 | 91 | from palm_tools.analysis.mmd_analysis import MMDInterGroupAnalysis, MMDInterUnitAnalysis
from palm_tools.analysis.mds_analysis import MDSAnalysis
from palm_tools.data_structure.trackset import TrackSets
import logging
import numpy as np
from palm_tools.post_processing.ts_post_processing import PostProcessingStepSeries
... |
16fe33a0abfc28c776d7e57dbd7e6b9ea8272f03f448cba69d505ef2f7999d14 | Python | 4,022 | 167 | """
Compute in-connection degree, in-synapse degree.
"""
import numpy as np
import pandas as pd
import pickle
def main():
Neuron = load_dict("../data/Neuron.pkl")
seg_id_list = Neuron["segment_id"]
n = seg_id_list.shape[0]
conn_fname = "../data/pyc_pyc_subgraph.csv"
conn_all_fname = "../data/pyc_all_synapse.cs... |
36cd3e3827850d73bc4f1654d350b346fc80a7662aaa767313daa99ca4c594b0 | Python | 4,022 | 101 | import cog
import tempfile
from pathlib import Path
import argparse
import cv2
import torch
from PIL import Image
import torch.nn.functional as F
from torchvision import transforms
from models.models import create_model
from options.test_options import TestOptions
from util.reverse2original import reverse2wholeimage
fr... |
0a1489ecb00a5cb77ae4b90543a91a178167ded99dad9da773605813b1c1260a | Python | 4,024 | 133 | import os
import random
import albumentations
import albumentations.pytorch
import numpy as np
import torchvision
from PIL import Image
class ResizeRandomCrop:
def __init__(self, img_size=320, scale_rate=8 / 7, p=0.5):
self.img_size = img_size
self.scale_rate = scale_rate
self.p = p
... |
248edb4e03ea161d049d10514bf9b56f1a9f75bcc17324d40f90a50a4c1b7c39 | Python | 4,024 | 128 | import math
import paddle.nn as nn
import paddle
num_classes = 93431
class SEBlock(nn.Layer):
def __init__(self, channel, reduction=16):
super(SEBlock, self).__init__()
self.avg_pool = nn.AdaptiveAvgPool2D(1)
self.fc = nn.Sequential(
nn.Linear(channel, channel // reduction),
... |
2553f8c48550e9ebfb5ccebee9d343ac7f4ade53d37e95820ee7d3f375da70cf | Python | 4,024 | 104 | """Public-API and CLI regressions for #800, part of #757."""
import gzip
from pathlib import Path
import random
import subprocess
import sys
import MACS3
import pytest
from conftest import macs3_env, no_core_dumps
HEADER = "@SQ\tSN:chr1\tLN:1000000\n"
def record(name="rev", flag=16, cigar="50M", pos=5000):
r... |
4edc4e08c34d3cb4528589f8b6e99a4bafaadced86fd6b35adcd5f7d4afcf5cc | Python | 4,024 | 120 | # Some part of the code was referenced from below.
# https://github.com/pytorch/examples/tree/master/word_language_model
import torch
import torch.nn as nn
import numpy as np
from torch.nn.utils import clip_grad_norm_
from data_utils import Dictionary, Corpus
# Device configuration
device = torch.device('cuda' if to... |
c3b22437216e99fd7f867597219ecb9718085848e19237081ee571e9bbc29322 | Python | 4,025 | 139 | #%% [markdown]
## Linking transcriptome and connectome via graph matching
# > A simple attempt to see if one 'ome can be aligned to the other 'ome
#
# - toc: true
# - badges: false
# - categories: [pedigo, graspologic]
# - hide: true
# - search_exclude: true
#%%
import os
import time
from pathlib import Path
import m... |
ad5af0007738dfff22bcd33926c802d46575d8f687ba1d088e8fc9eb2b36efc6 | Python | 4,027 | 111 | """
Handles outputting the model predictions
"""
from .handler import PredictionsHandler
class WritePredictionsHandler(PredictionsHandler):
"""
Collects batches of model predictions and writes all of them
to file at the end.
Parameters
----------
features : list(str)
List of sequence-... |
d13a89fe45e62c3820eadb4c6a1a8ba54dc211e0ef494692aaf7f9be8c73c45e | Python | 4,028 | 110 | import tensorflow as tf
EPSILON = 1e-12
#-------------------------------------------------------------------------
""" Non-saturating minimax loss
Goodfellow et al. Generative adversarial networks. NeurIPS, 2014
https://arxiv.org/abs/1406.2661 """
@tf.function
def minimax_D(real_output: tf.Tensor, fake_outp... |
f9a91e7a94105185417516789b21e0955a1bacd24aa2c699b7d56213d37b6130 | Python | 4,029 | 100 | from __future__ import print_function
import torch
import numpy as np
from PIL import Image
import numpy as np
import os
# Converts a Tensor into a Numpy array
# |imtype|: the desired type of the converted numpy array
def tensor2im(image_tensor, imtype=np.uint8, normalize=True):
if isinstance(image_tensor, list):
... |
b515772b1b7973df36624cef8ac689e8cb8e32979a3000c7baac8d287c4d9337 | Python | 4,031 | 122 | """
File: cmd_line_arguments.py
Created: 2020/03/19
Last Changed:
Author: M.Vochteloo
Copyright (C) 2020 M.Vochteloo
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version... |
97e6d4995b8ebd46ac28d030878cd3a054f8edb9dd4be87347bc06de2d59e237 | Python | 4,032 | 110 | import math
import torch
from torch.testing import assert_close
import pytest
from ..embeddings import SinusoidalEmbedding
# Testing NeRF Embedding: start with a simple range
# and see that it is embedded properly
batch_size = 4
num_freqs = 3
in_channels = 3
n_in = 2
max_pos = 10000
if torch.backends.cuda.is_built... |
c66086d0121bb9a315c8242c5b6db9c790586023934b50b6d322124e15153f0e | Python | 4,033 | 119 | from Lif_Parameters import *
from Lif_Equations import eqs_LIF
seed(val)
#####################################
# Initialize the neuronal populations
#####################################
# ------- Layer 0 -------
l0 = NeuronGroup(n_cells, eqs_LIF, method='exponential_euler', threshold='vm>v_th', reset='vm=v_r', refra... |
f515e51de21a983e0c35743417a615ee6b704531d0f734494a851d7779af911e | Python | 4,033 | 113 | """Generic dataset download helpers for CROPro CLI.
This module intentionally contains no dataset-specific URLs or presets. Dataset
specific download behavior can be provided through local dataset plugins.
"""
from __future__ import annotations
import urllib.parse
import urllib.request
import zipfile
from dataclasse... |
f2fe94cd2d5e1ac3a4250b8758b455cdaf833d6df8897801c8d4092e1c35efe2 | Python | 4,035 | 178 | # %% [markdown]
# #
import os
import colorcet as cc
import matplotlib as mpl
import matplotlib.pyplot as plt
import networkx as nx
import numpy as np
import pandas as pd
import seaborn as sns
from scipy.stats import rankdata
from sklearn.decomposition import PCA
from graspy.plot import heatmap, pairplot
from graspy... |
52e3f4650a9e1f7d1f986c24e1338e23b9831973c1eba5477ed7464aca414690 | Python | 4,037 | 100 | # Copyright 2021 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... |
572cb3e2c25688951a9adf8661813a356b5398e77ff39918eaac37b9b1ffd357 | Python | 4,037 | 116 | import numpy as np
from keras_preprocessing import image
def random_flip(img, mask, u=0.5):
if np.random.random() < u:
img = image.flip_axis(img, 1)
mask = image.flip_axis(mask, 1)
if np.random.random() < u:
img = image.flip_axis(img, 0)
mask = image.flip_axis(mask, 0)
retu... |
ad439a2178355be77c8dacfa257e570a68904cacdb5d47cf69f9ead8f8387c26 | Python | 4,038 | 113 | # ----------------------------------------------------------------------
# LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator
# https://www.lammps.org/ Sandia National Laboratories
# LAMMPS Development team: developers@lammps.org
#
# Copyright (2003) Sandia Corporation. Under the terms of Contr... |
3dbe438e86a8d94aabc0d4eaaa10e7f85b2334f5e3b6c745b4249a94b7cc167e | Python | 4,039 | 102 | import torch
from fairseq.models.bart import BARTModel
import argparse
from tqdm import tqdm
import os
from os.path import join
import logging
import time
def generate_TLDRs(bsz, count, datadir, outdir,
checkpoint_dir, checkpoint_file, test_fname,
beam, lenpen, max_len_b, min_l... |
36028a00d67c2c4a2fca8abbc687a0adf3fc94ec136b3e420596ea02c2cb6198 | Python | 4,042 | 124 |
import math
import glob
import argparse
parser = argparse.ArgumentParser(description='Create slurm jobs to merge gVCFs together in batches of 200')
parser.add_argument('list_of_vcfs', help='.txt file with list of path of VCFs to merge (only for chr15, this will be replaced for other chr numbers)')
parser.add_argume... |
4bbd8c4779abc89f3580b9528500b3e78fef59917aa66faa052f48b4faee27ec | Python | 4,042 | 145 | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from a2c_ppo_acktr.utils import AddBias, init
"""
Modify standard PyTorch distributions so they are compatible with this code.
"""
#
# Standardize distribution interfaces
#
# Categorical
class FixedCategorical(torch.distributions.Catego... |
93ba1fb9626bcc03eb278aaae77eccb5059888471fd3b3058731c9e838851315 | Python | 4,042 | 118 | from torch_geometric.loader import DataLoader
import pytorch_lightning as pl
from torch.utils.data import random_split
from torch.utils.data.distributed import DistributedSampler
from . import default_ds_params, default_graph_info
# from ..simulation.diffusion_models import generators, params_sampler
from ..simulation... |
eece9afb0553c3cef4f054275314eb7ccb97bdd4634cd6892bef2bd2aff1f8f6 | Python | 4,042 | 151 | #!/usr/bin/env python
###
# #%L
# Triangulated surface for deforming in 3D.
# %%
# Copyright (C) 2013 - 2023 University College London
# %%
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software wi... |
21caf85e289d9f3a448b549d2ef2261cc93b69362659dbd3e712596c5142980b | Python | 4,043 | 109 | # -*- coding: utf-8 -*-
import time
from collections import OrderedDict
import numpy as np
import torch
import torch.nn as nn
from torch.autograd import Variable
from utils.module_madd import compute_module_madd
class CModelHook(object):
def __init__(self, model, input_size, device):
assert isinstance(m... |
22561a94a15d3bcdf79aa9c51e20ad6f7ae7973974ca8647aa867d16a8201760 | Python | 4,044 | 82 | __author__ = 'tsungyi'
from . import _mask
# Interface for manipulating masks stored in RLE format.
#
# RLE is a simple yet efficient format for storing binary masks. RLE
# first divides a vector (or vectorized image) into a series of piecewise
# constant regions and then for each piece simply stores the length of
# ... |
fd2eb516230acf281635a5c26523b7af128cb85ae1cd83a95230d9275ac3baf1 | Python | 4,044 | 98 | from collections import defaultdict
from dataclasses import dataclass
from typing import List, Iterable, Tuple, Callable, Optional, Any, Dict
import sssom
from oaklib.datamodels.obograph import Node
from oaklib.datamodels.validation_datamodel import ValidationConfiguration, ValidationResult
from oaklib.interfaces.basi... |
374e0e65b42a99eb14fb60b8ba9ce793fb1eff81b1220dc75d565e2f6fdcb823 | Python | 4,045 | 69 | # A dictionary that contains templates of frequently used models or strings
library = {
# Adaptive exponential integrate & fire:
'adex': ('dV{0}/dt = (gL{0} * (EL{0}-V{0}) + gL{0}*DeltaT{0}*exp((V{0}-Vth{0})/DeltaT{0}) + I{0} - w{0}) / C{0} :volt\n'
'dw{0}/dt = (a{0} * (V{0}-EL{0}) -w{0}) / tauw{... |
8b517c42866f5d39ad0fc5e654ac9a173fe9c9b62378c04b54a8e6e1be057a68 | Python | 4,045 | 98 | # -*- coding: utf-8 -*-
"""
Created on Mon Dec 2 09:42:42 2019
@author: rjovelin
"""
import pysam
from debarcer.utilities import get_consecutive_items
from debarcer.utilities import GetContigs
def FindRegionsCoverage(bamfile, contig, min_cov, region_size, max_depth, ignore_orphans, stepper):
'''
(str, str... |
8b7b1a89e680b8a9566b1b8200e453b05e752ce8ed073385a51fd03798e4958e | Python | 4,047 | 126 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Provides methods for accessing the interface eAE API.
"""
import json
import stat
import os
import zipfile
import http.client as http
from subprocess import call
from uuid import uuid4
__author__ = "Axel Oehmichen"
__copyright__ = "Copyright 2017, Axel Oehmichen"
__c... |
89693413094cd2d99437e400b2c736f5a1ae64f738ef0e646f0f1285e885a4a4 | Python | 4,048 | 116 | import os
import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)
import numpy as np
from subprocess import Popen, PIPE
from IPython.core.debugger import *
import sys
from Bio.PDB import *
import pyflann
def test_alignment(target_pdb_fn, source_pdb_fn, aligned_pdb_fn, interface_dist = 10.0):
... |
ece6b3931cfeae8f2b4265ae093ae5222efa9359eb1aeac173b0aae79d351bf7 | Python | 4,055 | 85 | """
Model for a honeybee olfactory receptor (OR) type.
The receptor is modeled with a system of ODEs which govern the
fraction of unbound receptors (r0), the receptors bound to odorant i
(rb0, ..., rb2), and the receptors bound and activated by odorant i
(ra0, ..., ra2).
Was formulated, the model supports 3 active che... |
edea2f164fb6f0edc7b41341883b60b9747a28d71a8880c23a6ff171b0aab374 | Python | 4,055 | 112 | # Copyright 2020 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... |
2fa997ab2d7f7546ed4301c117bdb84024e94788f7fbe6c5ae69ddc75ecbe85e | Python | 4,056 | 107 | """
File: cmd_line_arguments.py
Created: 2020/11/09
Last Changed: 2020/11/12
Author: M.Vochteloo
Copyright (C) 2020 M.Vochteloo
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, eit... |
b65dd40bcfafadd26a562b903f18de858284788656d5e249093b3519204f5d5d | Python | 4,056 | 92 | import os
import synapseclient
import synapseutils
import argparse
import getpass
parser = argparse.ArgumentParser(description='Download RNAseq and genotypes of CMC.')
parser.add_argument('RNAseq_directory', help='Directory to download RNAseq data to')
args = parser.parse_args()
user = input("Synapse username:")
pas... |
e66565f8ff03f1247f11d0423e97a22ebff11642d238ed56101ac2e74d0f5eff | Python | 4,056 | 145 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import sys
import unetsl.data
import unetsl.config
from unetsl.cli_interface import getFilePrompt
def getNumberList(inp):
print(inp)
values = inp.split();
print(values)
x = []
for v in values:
try:
d = float(v.rstrip(","))
... |
cb2d26ab9c3639128c5ae12b1141aa2c69389c115bc6b18081fb63171325a117 | Python | 4,057 | 140 | #!/usr/bin/env python
# coding: utf-8
#
# Author: Kazuto Nakashima
# URL: http://kazuto1011.github.io
# Created: 2017-11-19
from __future__ import absolute_import, print_function
from collections import OrderedDict
import torch
import torch.nn as nn
import torch.nn.functional as F
try:
from encoding.nn ... |
535355129f5e90ed8b56daa33b25bb81c3274591f94f13e975da6510ab336154 | Python | 4,059 | 125 | from bonelab.util.aim_calibration_header import get_aim_density_equation
import numpy as np
import vtkbone
import os
from vtk.util.numpy_support import vtk_to_numpy
from glob import glob
from torch.utils.data import Dataset
class HRpQCTAIMDataset(Dataset):
def __init__(self, data_dir, data_pattern, transform=No... |
c51bf970932e2680340b19c30ef6455d0fd30c131f88eae9f92c4b645a929d35 | Python | 4,066 | 115 | # Copyright (c) 2026 Computer Vision Center (CVC) at the Universitat Autonoma
# de Barcelona (UAB).
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
"""Verify that the Boost dependency used to build carla.libcarla is 1.90.0.
ue5-dev builds Boost vi... |
2ee8752bf35b715d38dbe46a7bdefae75ac2cfc74305a4a45156fc7133ab6cdc | Python | 4,070 | 120 | from __future__ import division
import argparse
import numpy as np
import os
import os.path as osp
import sys
sys.path.append(osp.join(sys.path[0], '..'))
import time
import torch
import warnings
warnings.filterwarnings("ignore", category=UserWarning)
import models
from mmcv import Config
from mmdet import __version_... |
3330342a05eb445bf74a34de8cea3f4ea29bc55a6f09d931d86263e307a68765 | Python | 4,070 | 123 | import argparse
import os
import autosklearn.classification
import joblib
import medmnist
import numpy as np
from medmnist import INFO, Evaluator
from medmnist.info import DEFAULT_ROOT
def main(data_flag, time, input_root, output_root, run, model_path):
time = time * 60 * 60
info = INFO[data_flag]
... |
c96d118829f729f0fd44b48a7e4a8408f1fedf9771e041be90ce9a91acf04e47 | Python | 4,071 | 117 | nC = 3 # number of channels / colors
# nR = 5
nR = 1 # number of rounds (except the last dT labeling)
roundRef = -1 # round containing the cell reference; use -1 for the last round
cellch = 2 # channel containing cell reference
img_size = (2048, 2048)
sigma = 2 # estimate size of spots to detect
# shif... |
1c5d6d007d2caa3b4cd75e1f7e855880ed112067b2b868ab299bb2a39f07d73c | Python | 4,072 | 117 | from constants.enumerates import ElectricalAppliances
WINDOWS = {
'NFED': {
ElectricalAppliances.MICROWAVE: 50,
ElectricalAppliances.KETTLE: 50,
ElectricalAppliances.FRIDGE: 350,
ElectricalAppliances.WASHING_MACHINE: 150,
ElectricalAppliances.DISH_WASHER: 450,
},
'S... |
2f3a8b5c1dd9447fe5034858d75b4a503bbc363f61e952f352771eed34b5b6ab | Python | 4,072 | 106 | import torch
from ..builder import BBOX_SAMPLERS
from ..transforms import bbox2roi
from .base_sampler import BaseSampler
@BBOX_SAMPLERS.register_module()
class OHEMSampler(BaseSampler):
r"""Online Hard Example Mining Sampler described in `Training Region-based
Object Detectors with Online Hard Example Mining... |
e233257006d177116a03ac858da8fab5ad52b59a8c62543d365f137da2715295 | Python | 4,072 | 141 | #
# A simple file for converting any XML file via an XSL stylesheet
#
# Author: Padraig Gleeson
#
# This file has been developed as part of the neuroConstruct project
# This work has been funded by the Medical Research Council and Wellcome Trust
#
#
import sys, os
# This can be changed to any local file or a... |
e95a0995ef460ebb81c5c3d9b388ea7db3bbf1005295aa2dca46d72b7e9997cd | Python | 4,072 | 157 | # -*- coding: utf-8 -*-
"""
Created on Mon Feb 14 15:11:48 2022
@author: N.V
"""
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from matplotlib.animation import FuncAnimation
import os
# note that this must be executed before 'import numba'
os.environ['NUMBA_DISABLE_INTEL_... |
248d7e38d63acf86562cec6d4d3dde5fc88b63c9c4a3ba47a63fe03a4f59417b | Python | 4,073 | 109 | """
File: filter_technical_covariates.py
Created: 2020/10/13
Last Changed:
Author: M.Vochteloo
Copyright (C) 2020 M.Vochteloo
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either... |
8ca86ef8b56be8788c9ce8664a3dc9dd72bc0a76f27f3ef6201f62dd750739ad | Python | 4,073 | 137 | import os
import numpy as np
import torch
from torchvision import transforms
from torch.utils.data import DataLoader, Dataset
classes = {'airplane' : 0, 'bathtub' : 1, 'bed': 2, 'bench': 3, 'bookshelf':4, 'bottle':5, 'bowl' : 6, 'car':7, 'chair' : 8, 'cone' : 9, 'cup':10, 'curtain':11
, 'desk':12, 'door':1... |
7306c94b1d2cce32974a729ebec3e253045e5fccc095d36c9c050932b1d7a9b6 | Python | 4,074 | 123 | """
(stability)
1) edge mask of original graph by some explainer
2) edge mask of perturbed graph by some explainer
(faithfulness)
1) edge mask of original graph by some explainer
2) ground truth edge mask
Compute importance score
"""
import random
import torch
from torch_geometric.data import Data
from graphxai.uti... |
8ce2100e75730bd7524ecf50e3cf1a4991a23167fa8a0cf6e6d25a671a7d991b | Python | 4,075 | 126 | # Copyright (c) 2015-present, Facebook, Inc.
# All rights reserved.
"""
A script to run multinode training with submitit.
"""
import argparse
import os
import uuid
from pathlib import Path
import main as classification
import submitit
def parse_args():
classification_parser = classification.get_args_parser()
... |
f999d4be30b9adc3cbad49f64ba87fb9addf5bfc6d93ab8dde425b100d6a74c3 | Python | 4,076 | 105 | #%%
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from pymaid_creds import url, name, password, token
from data_settings import data_date, pairs_path
import pymaid
rm = pymaid.CatmaidInstance(url, token, name, password)
from contools import Celltype, Celltype_Analyzer, P... |
20b380c900886a7e1c8e8bcdaa559536278da2b22ca271dccc93879dc29aa267 | Python | 4,077 | 112 | from collections import defaultdict
import numpy as np
import pandas as pd
from sklearn.metrics import auc, roc_curve
from sklearn.utils import resample
from tabulate import tabulate
from tqdm import tqdm
white = "White"
asian = "Asian"
black = "Black"
def get_boostrap_ci_for_split_race_experiment(
targets_race... |
057838e7d41dd8422d8f8806c7f8d35f76387b142e4bb43fa04c2557a2335d5c | Python | 4,078 | 177 | # %% [markdown]
# ##
import os
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from matplotlib.patches import Circle
from mpl_toolkits.axes_grid1 import make_axes_locatable
from mpl_toolkits.mplot3d.art3d import Poly3DCollection
from scipy.integrate... |
24ab61d7e4cb689b1e61b78a199021bd094fb63b4e6a27575b0acf5d367b4347 | Python | 4,078 | 134 | import logging
from typing import Tuple, Union
import anndata
import numba
import numpy as np
import pandas as pd
import scipy.sparse as sp_sparse
logger = logging.getLogger(__name__)
def _compute_library_size(
data: Union[sp_sparse.spmatrix, np.ndarray]
) -> Tuple[np.ndarray, np.ndarray]:
sum_counts = data... |
554b6b202d2b29ff5a6310b67f34553bdaabc05b61e9b64050e8a537387d2dfa | Python | 4,078 | 138 | """
StyleMapGAN
Copyright (c) 2021-present NAVER Corp.
This work is licensed under the Creative Commons Attribution-NonCommercial
4.0 International License. To view a copy of this license, visit
http://creativecommons.org/licenses/by-nc/4.0/ or send a letter to
Creative Commons, PO Box 1866, Mountain View, CA 94042, U... |
55fc78dbac64752c4153bd83f9aee7f5715a121e03e427b3fd1fa659e5614771 | Python | 4,078 | 119 | # Copyright 2022 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... |
dfc442e32574550fae5f19847dccb5a865c2bbb4524e44b952137ed192a88bf6 | Python | 4,079 | 98 | # Copyright 2022 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... |
99ab5735d571a7ef8557808c70d110bcd475e5a2485b85205bf9c6eef54a60f0 | Python | 4,080 | 83 | import torch
import torch.nn as nn
import torch.nn.functional as F
from core.models.base_models import Enc, FCAttention, get_xception_a
from core.nn import _ConvBNReLU
__all__ = ['DFANet']
class DFANet(nn.Module):
def __init__(self, nclass, backbone='', aux=False, jpu=False, pretrained_base=False, **kwargs):
... |
c6b4f01b307dc2d8c683e4ffdb05e257a389e5a0b0a0e08429b61c9d95899d2b | Python | 4,080 | 112 | from utils.ArticlesHandler import ArticlesHandler
from utils import solve, embedding_matrix_2_kNN, get_rate, accuracy, precision, recall, f1_score
from utils.Trainer_graph import TrainerGraph
from utils import Config, accuracy_sentence_based
import time
import numpy as np
# from utils.postprocessing.SelectLabelsPostpro... |
4cbe5f71278bb81723438c720b634279cf107cb5e378b9bfd6c07033a1708d24 | Python | 4,083 | 113 | import pandas as pd
import pybedtools
import logging, os
def log_message(*message):
"""write message to logfile and stdout"""
if message:
for i in message:
logging.info(i)
print(i)
def query_alias(aliases, gene):
"""check if gene is in list of aliases"""
# check if va... |
bce6b5b32deffd1cc6bf2b6bf47a33ac4cfacdf5d4193aa5603a295f8baefffe | Python | 4,084 | 98 | #!/usr/bin/env python
# Copyright 2015 Minhua Wu
# Apache 2.0
# convert acronyms in swbd dict to fisher convention
# IBM to i._b._m.
# BBC to b._b._c.
# BBCs to b._b._c.s
# BBC's to b._b._c.'s
import argparse,re
__author__ = 'Minhua Wu'
parser = argparse.ArgumentParser(description='format acronyms to a._b._c.')
p... |
fd782d5a129822a20f604c7b8905a911f5d966bac85790c200edcabaea6279a9 | Python | 4,085 | 102 | import jax.numpy as jnp
import xarray as xr
try:
DPHOX_IMPORTED = True
from dphox.device import Device
from dphox.pattern import Pattern
except ImportError:
DPHOX_IMPORTED = False
from ..fdfd import FDFD
from ..typing import Callable, Iterable, List, Optional, Size, Union
class Component:
def __... |
098b774a15763dc503b673a5be1ab75ea2b9e1e153aa70ad3ade92053e032887 | Python | 4,086 | 102 | # Copyright 2021 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... |
93485b66e223ae6cf898cecd4d7cc2f65a4efca467ca2e65dc538154933b6e94 | Python | 4,086 | 108 | import autograd.numpy as anp
from .base import BaseModel
# ODE Model constructor class
# Used as constructor for SUR
class ODEModel(BaseModel):
def __init__(self, kinetics: bool = True):
super(ODEModel, self).__init__(kinetics)
# FSCV experiment parameters
def initialize(self, bursts: list, f:... |
659869484bd6911002636a49e0a269b85057878827680a88c5c6b41be3b86a2d | Python | 4,088 | 122 | # Copyright 2022 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... |
982e9a3cb2393044674faad7a10575c27366b282f7b836e2a0ca76a8b62f61bb | Python | 4,088 | 122 | # Copyright 2021 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... |
68288612efbab7287fe36dd32887fc2cc8ad413f58ba4f4b7330b361effc36cf | Python | 4,090 | 120 | import os
import torch
import numpy as np
import pandas as pd
from torch_geometric.data import Data
from graphxai.utils import Explanation, edge_mask_from_node_mask, aggregate_explanations
#def load_graphs(dir_path: str, smiles_df_path: str):
def load_graphs(datapath: str):
'''
Extracts datasets from a forma... |
90b3f486c710ab4147a9e18bfe12a0351c0d5943a8dcff97bde6c1fef814cbec | Python | 4,090 | 135 | #%%
import pandas as pd
from pathlib import Path
import numpy as np
import matplotlib.pyplot as plt
# %%
csv_dir1 =Path("fit_csvs_short/")
csv_dir2 =Path("fit_csvs_skipped_split/")
#%%
df_list=[]
for csv_file in sorted(csv_dir1.glob("*/*.csv")):
df_list.append(pd.read_csv(csv_file,index_col=0))
full_df1=pd.concat... |
d525b0fbab6923e0be6db69ec46bbe0614f842b9022df017b9ffc1981e114f3c | Python | 4,092 | 98 | # basic imports
import os
import pickle
import numpy as np
# framework imports
from cobel.agents.sfma import SFMAAgent
from cobel.interfaces.gridworld import InterfaceGridworld
from cobel.analysis.rl_monitoring.replay_monitors import ReplayMonitor
def single_run(world: dict, mode: str = 'default', trials: int = 20, t... |
f81f549e5eb6236629dc06aa04e23a8a00c584bdd35abc9949cdaf68e3544569 | Python | 4,092 | 102 | import numpy as np
import itertools
import torch
import torch.nn.functional as F
def resample(x, res_scale, axis, output_shape=None):
"""A module for generic n-dimentional interpolation.
For 1D and 2D inputs, the ``resample`` function uses PyTorch’s built-in spatial interpolators
for efficiency, applying... |
97861d0471f48fffa63236da2a7e821f91a3bde1f5e791ed511f514c9b30a653 | Python | 4,093 | 111 | import base64
import logging
from copy import deepcopy
from itertools import product
from random import shuffle
from typing import Iterator, List, Set, Tuple
from oaklib import BasicOntologyInterface
from oaklib.datamodels.obograph import (
ExistentialRestrictionExpression,
LogicalDefinitionAxiom,
)
from oakli... |
fa2aae641f116063172a40aa7240da0fa294d15db6e65ac204da92f4d14de580 | Python | 4,096 | 99 |
import cv2
import torch
import fractions
from PIL import Image
import torch.nn.functional as F
from torchvision import transforms
from models.models import create_model
from options.test_options import TestOptions
from insightface_func.face_detect_crop_multi import Face_detect_crop
from util.videoswap_multispecific im... |
6e96f58afefe9c99189215e7e5982977534de97441b62a3b29dfa2efcda91db6 | Python | 4,098 | 111 | #!/usr/bin/env python3
#
# Copyright (c) 2018 Hyeshik Chang
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modi... |
9a6f2f08246fde0d799959052aed89fd78a94fc7f55c1450dd81d7659efdb98f | Python | 4,099 | 132 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
class EDANet(nn.Module):
def __init__(self, classes=2, aux=True):
super(EDANet, self).__init__()
self.layers = nn.ModuleList()
self.dilation1 = [1, 1, 1, 2, 2]
self.dilation2 = [... |
2340eb5b06d74097ca2f7a1650972be0e6f96c35c4b03cc5d648949bb470cc63 | Python | 4,100 | 115 | '''
@author: Mahbub Ul Alam (mahbub@dsv.su.se)
@version: 1.0+
@copyright: Copyright (c) Mahbub Ul Alam (mahbub@dsv.su.se)
@license : MIT License
'''
'''@file early_sepsis_detector.py
run this file to go through the complete neural net training, testing and evaluating procedures,
look at the 'early_sepsis_detector_con... |
80ce73938f821dc6f03276f6f7c9d9cb6a0dd88a935dfe2f189bf9d60e79416e | Python | 4,100 | 113 | # Copyright 2021 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... |
3dc5e35a26ee0967285857826cd4441206075bd24c8d52669c4975403b2948a7 | Python | 4,102 | 105 | '''
Track anterior and posterior ends.
The first frame of each trial is matched to subsequent frames.
Remember that "anterior" and "posterior" refer to two unidentified ends here; they could be posterior and anterior.
Results are saved in um, measured along the main axis and the normal axis.
'''
import os
import numpy ... |
22c47060c1acb9c67f3acaa608ad7ada3514cbbbd24d2ff77b419ac9797d723b | Python | 4,104 | 94 | # Copyright 2022 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... |
0890fdb234426a4776f86e9c7e2e14585fd1900fce21d1a18e26f3f575abc744 | Python | 4,105 | 58 | # -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# NO CHECKED-IN PROTOBUF GENCODE
# source: nre/grpc/protos/common.proto
# Protobuf Python Version: 5.29.0
"""Generated protocol buffer code."""
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor... |
32ed825b12059bd4686b6dc5979a2feb3bbd59c5488f86075467f5c87a9e6d13 | Python | 4,105 | 110 | import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.ticker as mtick
from matplotlib import gridspec
import matplotlib.colors as colors
import seaborn as sns
from scipy import stats
sns.set_style("ticks")
hfont = {'fontname':'Myriad Pro'}
from matplotlib import colors
# de... |
64e3fe65e3d7b0d68a9d055d6b6e6abf773144849b33ab5f62bfe48f8da50462 | Python | 4,108 | 91 | # Copyright 2021 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... |
3681d9a21f10bf7a275290f15568d55220d9c9ff39cab8cc09f69d97e8f17df1 | Python | 4,109 | 114 | import mne
import numpy as np
from mne.viz import plot_epochs_image, plot_compare_evokeds
from scipy.stats import sem
def _standard_error(x):
"""
Compute confidence interval bands based on standard error.
Parameters
----------
x : array of shape (n_observations, n_times)
The signal obser... |
db436e8dfcc15d5bdfd6276a028ea776facc7e0bf8fd444a97511ab67a7bb7a0 | Python | 4,109 | 162 |
import numpy as np
import torch
import torch.nn as nn
from torch.utils.data import Dataset, DataLoader
import torch.nn.functional as F
import torch.optim as optim
torch.backends.cudnn.enabled = False
torch.manual_seed(42)
class TDSNet(nn.Module):
def __init__(self):
super(TDSNet, self).__init__()
self... |
4d6c801ade42714063ab00ad867cd6ef43a3fbaa0f76752fecd75eeb16e03150 | Python | 4,110 | 111 | """
Copyright 2020 - by Jerome Tubiana (jertubiana@gmail.com)
All rights reserved
Permission is granted for anyone to copy, use, or modify this
software for any uncommercial purposes, provided this copyright
notice is retained, and note is made of any changes that have
been made. This softwar... |
f195d67a670f499c848b5c6b893bfd4f821440ffe66809e13a92dd03189f2238 | Python | 4,112 | 107 | # Copyright 2022 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... |
bb42277853ead52f6463108e33a3d8045f6a8612d9cbaa22986047bf42590ce8 | Python | 4,114 | 122 | '''
Figure 7.
Fit to the example.
'''
from brian2 import *
import yaml
from file_management import *
from pylab import *
import matplotlib.font_manager as fm
import os
from fitting import *
from plotting import *
from matplotlib import gridspec
fontprops = fm.FontProperties(size=18)
width, height = 5, 7
t1 = -50*ms
... |
8516971832ee29777cc124a571dbba0cb88d2cfbd05bc0eff67056841e3f93ab | Python | 4,116 | 127 | import numpy as np
from tqdm import tqdm
import scipy.io
from dipy.io.stateful_tractogram import StatefulTractogram, Space
import nibabel as nib
from AFQ.data.utils import BUNDLE_MAT_2_PYTHON
# This dictionary is used to convert the names of the bundles
# from old pyAFQ bundle names to the new pyAFQ bundle names.
... |
25a1b5b52349c989a04e6bfe4f554fff1f5dbcb4acd2e2142029da628220b2ce | Python | 4,117 | 146 | '''
This script was used to create the test QSAR models in this folder.
Data is QSPRpred tutorial data, which can be downloaded from the following link:
https://1drv.ms/u/s!AtzWqu0inkjX3QRxXOkTFNv7IV7u?e=PPj0O2
'''
import os
import pandas as pd
from qsprpred.data import QSPRDataset
from qsprpred.data.descriptors.finge... |
8d78ecb055fbcc85a5e9f6652ade2a6b03161dab96f01a656a3b376d4a9bae4c | Python | 4,117 | 120 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import multiprocessing
import numpy as np
import tensorflow as tf
from tflib.data.dataset import batch_dataset, Dataset
_N_CPU = multiprocessing.cpu_count()
def memory_data_batch_dataset(memory_data_dict,... |
6b0c0a04633aa2bff9b9053ee10f6496ea650c40d046a6a1abdf99cd0feb81ab | Python | 4,118 | 107 | # Copyright 2022 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... |
85526bba3d4f3b48fc99897efbebf0b63cb89f415f99a19f35c0225683f6585e | Python | 4,118 | 131 | from __future__ import division
from __future__ import print_function
from __future__ import absolute_import
import os
import models
import traceback
import numpy as np
import tflib as tl
import tensorflow as tf
os.environ['CUDA_VISIBLE_DEVICES'] = '0'
""" param """
epoch_ = 25
batch_size = 64
lr = 0.0002
gpu_id = 0... |
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